Mobile technology continues to expand and continues to become more important to our everyday lives. As a result of mobile communications, a user and/or their mobile device may need to be able to accurately identify the device's geo-location. Mobile devices are equipped with a variety of sensors and measuring devices and are often in communication with external sensors or applications, providing different ways to find a user's location. The most straightforward and accurate way to find one's location is to use a Global Positioning System (GPS) sensor in the device. The sensor receives signals from a series of low earth orbit geosynchronous satellites and finds where that device is located on the globe. Using a GPS receiver in a mobile device has a power expense that is often very high, especially with the limited power resources of a mobile device.
A second approach to positioning allows mobile devices to constantly report back to a system or server, all the Wi-Fi Service Set Identifiers (SSIDs) that the mobile device may encounter at a specific location. The location information where those SSIDs are located may have been previously acquired from GPS signals, and that information is stored in a database which identifies the Wi-Fi SSID environment at given locations around the globe. Using a matching algorithm the mobile device can match the device's location to the actual location that has been previously recorded. This approach assumes that the mobile device is also at that location because of the match in SSIDs. Wi-Fi signals allow the mobile device to generally locate its position, and then by accessing the historic database information, the device can make a good estimation of where it is located based on the sensed Wi-Fi SSIDs. Wi-Fi position location requires less power than GPS because it only has to monitor the Wi-Fi signals it receives.
A third approach for geo-location for a mobile device, which is less accurate but has even lower power consumption than Wi-Fi, is cellular signal identification/triangulation. Cellular signal identification/triangulation allows the mobile device to identify the cell tower signals it is receiving at any given time and then query a database to determine a general location fitting the criteria where those particular towers would be located. As will be appreciated by those skilled in the art, other methods of geo-location are available, such as the use of BlueTooth™, iBeacons, and others, each with its own power consumption requirements.
Each of these geo-location methods initially use coarse-grained location algorithms to speed up the search by reducing search space. For example, IP addresses assigned by network providers may indicate coarse geographic regions, which may be used as a low or zero energy location sensor. In this manner, the device has a broad geographic region to begin its location identification.
Each of these methods have advantages and limitations. More accuracy usually requires more power, but accuracy is not always the most important criteria. Conversely, lower power usage implies less accuracy and may not always be sufficient for a given application. Accordingly, a need exists for a way to minimize sensor usage to optimize power usage while ensuring sufficient accuracy based on the application.